Triple

T12677169
Position Surface form Disambiguated ID Type / Status
Subject Linha do Norte E302845 entity
Predicate hasMajorStation P1071 FINISHED
Object Entroncamento E374173 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Entroncamento | Statement: [Linha do Norte, hasMajorStation, Entroncamento]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Entroncamento
Context triple: [Linha do Norte, hasMajorStation, Entroncamento]
  • A. Entroncamento chosen
    Entroncamento is a Portuguese railway junction city in the Centro Region, known for its strategic location on the country’s main rail lines.
  • B. Encruzilhada
    Encruzilhada is a neighborhood in the city of Recife, Brazil, known for its busy commercial areas and urban residential character.
  • C. Felling
    Felling is a town in Tyne and Wear, England, situated on the south bank of the River Tyne near Gateshead and Newcastle upon Tyne.
  • D. Divisadero
    Divisadero is a nonlinear, character-driven novel by Michael Ondaatje that interweaves past and present across California and France to explore memory, identity, and the fractures within a makeshift family.
  • E. Divisadero
    Divisadero is a popular lookout and tourist stop in Mexico’s Copper Canyon region, known for its dramatic canyon views and access to scenic train routes.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69d7bdee64a08190801c6d470aefd723 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d961b0d9c88190a05d6cbcb7a1642d completed April 10, 2026, 8:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69f671a341288190822fae2469efea09 completed May 2, 2026, 9:50 p.m.
Created at: April 9, 2026, 5:20 p.m.